code: def multi_gpu_launcher(args):
      import torch.distributed.run as distrib_run
  
      current_env = prepare_multi_gpu_env(args)
      if not check_cuda_p2p_ib_support():
          message = "Using RTX 4000 series which doesn't support faster communication speedups. Ensuring P2P and IB communications are disabled."
          warn = False
          if "NCCL_P2P_DISABLE" not in current_env:
              current_env["NCCL_P2P_DISABLE"] = "1"
              warn = True
          if "NCCL_IB_DISABLE" not in current_env:
              current_env["NCCL_IB_DISABLE"] = "1"
              warn = True
          if warn:
              logger.warning(message)
  
      debug = getattr(args, "debug", False)
      args = _filter_args(
          args,
          distrib_run.get_args_parser(),
          [
              "--training_script",
              args.training_script,
              "--training_script_args",
              args.training_script_args,
          ],
      )
      with patch_environment(**current_env):
          try:
              distrib_run.run(args)
          except Exception:
              if is_rich_available() and debug:
                  console = get_console()
                  console.print(
                      "\n[bold red]Using --debug, `torch.distributed` Stack Trace:[/bold red]"
                  )
                  console.print_exception(
                      suppress=[__file__], show_locals=False
                  )
              else:
                  raise
  
imports: import argparse
  import importlib
  import logging
  import os
  import subprocess
  import sys
  from pathlib import Path
  import psutil
  import torch
  from accelerate.commands.config import default_config_file, load_config_from_file
  from accelerate.commands.config.config_args import SageMakerConfig
  from accelerate.commands.config.config_utils import DYNAMO_BACKENDS
  from accelerate.state import get_int_from_env
  from accelerate.utils import ComputeEnvironment, DistributedType, PrepareForLaunch, _filter_args, check_cuda_p2p_ib_support, is_bf16_available, is_deepspeed_available, is_npu_available, is_rich_available, is_sagemaker_available, is_torch_version, is_tpu_available, is_xpu_available, patch_environment, prepare_deepspeed_cmd_env, prepare_multi_gpu_env, prepare_sagemager_args_inputs, prepare_simple_launcher_cmd_env, prepare_tpu
  from accelerate.utils.constants import DEEPSPEED_MULTINODE_LAUNCHERS, TORCH_DYNAMO_MODES
label_desc: Use image node_id 4 for calling a global function with example usage: multi_gpu_launcher(args) without return types